General
Spectroscopy is a method of measurement of the absorption and emission of electromagnetic waves by substances. When polychromatic light is directed at a sample, the sample attenuate different wavelengths of the electromagnetic spectrum in a specific way. This allows different materials to be readily identified by their spectral signature. For example, helium gas was first discovered by identification of it's unique signature in the sun's spectrum. The near infrared (NIR) region of the electromagnetic spectrum is particularly useful for analyzing samples of complex composition.
The said NIR region lies between the visible region and the infrared region of the electromagnetic spectra extending from 700 to 2600 nanometers. The bulk of NIR spectrum arise as a result of vibrational overtone stretches of the OH, NH, and CH groups of chemical bonds which are present in natural and man made products such as blood serum, plastics, tobacco and food products.
Present day near infrared spectroscopy is an analytical technique of wide applicability and requiring minimum sample preparation. Sampling can be performed without contact, generally requires no sample pre-treatment or separation techniques. The major advantage of NIR spectroscopy lies in its large signal to noise ratio, making it possible to analyze even trace constituents accurately, without the use of expensive Fast Fourier Transform analyzers (FFT). Furthermore, modern statistical analytical methods such as expert chemometric models, coupled with specialized sampling accessories such as fiber optic probes and flow cells, allow a wide variety of materials and mixtures to be readily analyzed in the NIR region of the spectrum. Expert chemometrics modelling allows multicomponent analysis of complex mixtures, or matrices, based on the knowledge of the underlying spectroscopy. Special algorithms allow an analyzer to measure qualities such as shelf life, tackiness, taste, and uniformity in addition to sample composition, in a non-invasive manner.
Minimal sample preparation and rapid analysis yield strong advantages over the conventional laboratory methods of chemical analysis. Laboratory methods of chemical analysis, though very accurate, can be labor intensive and time consuming. These drawbacks coupled with the possibility of sample contamination by human errors make NIR spectroscopy a desirable analytical tool. However, spectroscopic analysis methods can only yield results that are as accurate as the primary calibration method used to calibrate the analyzer. But by continuous calibration using all possible sample types within a measurement, errors can be minimized to yield a high degree of confidence in the method.
There are many areas in which NIR spectroscopy is successfully applicable. These include: the tobacco industry, pulp and paper industry, petrochemicals, biomedical, pharmaceutical, foods and beverages. The bio-medical industry is a particularly interesting field of application. NIR spectroscopy has been very successful as a fundamental analytical technique for effecting biomedical assays. Multiwavelength NIR spectroscopy, combined with sophisticated data analysis technics based on multivariate statistics, offer an attractive alternative to conventional analysis methods. The recent developments in Neural Network technology has added the advantage of nonlinear modelling for analysis of samples exhibiting high variability.